Overview

We are seeking a highly skilled AI & ML Engineer to join our innovative team. In this role, you will lead the development, optimization, and deployment of advanced machine learning and artificial intelligence models. You will drive state-of-the-art research, build scalable pipelines, and collaborate with cross-functional teams to translate business needs into effective ML solutions.

This position offers the opportunity to work on cutting-edge technologies in a dynamic, fast-paced environment, contributing to impactful projects that power next-generation AI applications.
Project Overview:

Responsibilities:
  • Design, implement, and optimize machine learning and AI models, including classification, regression, clustering, and agent tuning.
  • Experiment with the latest methods, frameworks, and architectures to enhance model performance and efficiency.
  • Develop robust, scalable ML pipelines for training, validation, and inference.
  • Deploy ML models into production environments (cloud or on-prem), ensuring high reliability, low latency, and scalability.
  • Apply MLOps best practices including CI/CD, monitoring, automated retraining, and model registry management.
  • Partner with data engineering teams to source, clean, and transform large datasets for model training and inference.
  • Ensure high data quality, perform feature engineering, and support real-time data integration processes.
  • Work closely with data scientists, software engineers, and product managers to align ML solutions with business goals.
  • Clearly communicate complex technical results to both technical and non-technical stakeholders.
  • Provide technical guidance and mentorship to junior ML engineers and data scientists.
  • Contribute to establishing team best practices, code reviews, and architectural decisions.
Nice To Have:
  • Experience with agentic frameworks like LangChain or LangGraph
Required Qualifications:
  • 5+ years of professional experience in machine learning, AI engineering, or related fields.
  • Master’s degree in Computer Science, Machine Learning, Physics, or related field; PhD preferred.
  • Proficient in Python and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
  • Strong understanding of algorithms, statistics, probability, and linear algebra.
  • Hands-on experience with data pipelines and ETL tools (e.g., Spark, AWS Lambda, AWS Glue).
  • Practical experience with cloud platforms, preferably AWS.
  • Solid software engineering fundamentals including version control (Git), testing, and design patterns.
  • Demonstrated success in deploying ML models into production at scale.
  • Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
  • Excellent analytical, problem-solving, and communication skills.
  • Ability to work autonomously and collaboratively within a fast-paced, cross-functional team environment.
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